We follow the same benchmark in [1]}.
We use the same three datasets \(\mathcal {D}_\text{in}\)  for training and evaluating: (i) 20News refers to the 20 Newsgroups dataset that contains news articles with 20 categories.
(ii) SST denotes Stanford Sentiment Treebank [2]}, a collection of movie reviews for sentimental analysis.
(iii) TREC consists of 5, 952 individual questions with 50 classes.
Finally, WikiText-2 is a corpus of Wikipedia articles used for language modeling. To fairly compare with [1]}, we also use its sentences as the auxiliary OOD examples \(\mathcal {D}_\text{out}^{\text{train}}\)  during the training.
